The impact of algorithmic technologies on healthcare

• Titel: The impact of algorithmic technologies on healthcare
• Mitwirkende: Dubey, Parul [HerausgeberIn]
• Mitwirkende: Madankar, Mangala [HerausgeberIn]
• Mitwirkende: Dubey, Pushkar [HerausgeberIn]
• Mitwirkende: Hung, Bui Thanh [HerausgeberIn]
• Verf.angabe: edited by Parul Dubey, Mangala Madankar, Pushkar Dubey, Bui Thanh Hung
• Verlagsort: Hoboknen, NJ ; Beverly, MA
• Verlagsort: Hoboknen, NJ ; Beverly, MA
• Verlag: Wiley
• Verlag: Scrivener
• Jahr: 2025
• Jahr: 2025
• Umfang: 1 online resource (480 pages)
• Gesamttitel/Reihe: Machine Learning in Biomedical Science and Healthcare Informatics
• Fussnoten: Online resource; title from PDF title page (John Wiley, viewed February 18, 2025)
• ISBN: 978-1-394-30549-0
• ISBN: 1-394-30549-4
• ISBN: 978-1-394-30546-9
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1921170573
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext
• Lokale URL UB: Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg
• Bibliothek/Idn: UW / m4696546470
• Lokale URL Inst.: Zum Volltext

Abstract

The book explores the fundamental principles and transformative advancements in cutting-edge algorithmic technologies, detailing their application and impact on revolutionizing healthcare. This book provides an in-depth account of how technologies such as artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) are reshaping healthcare, transitioning from traditional diagnostic and treatment approaches to data-driven solutions that improve predictive accuracy and patient outcomes. The text also addresses the challenges and considerations associated with adopting these technologies, including ethical implications, data security concerns, and the need for human-centered approaches in algorithmic medicine. After introducing digital twin technology and its potential to enhance healthcare delivery, the book examines the broader effects of digital technology on the healthcare system. Subsequent chapters explore topics such as innovations in medical imaging, predictive analytics for improved patient outcomes, and deep learning algorithms for brain tumor detection. Other topics include generative adversarial networks (GANs), convolutional neural networks (CNNs), smart wearables for remote patient monitoring, effective IoT solutions, telemedicine advancements, and blockchain security for healthcare systems. The integration of biometric systems driven by AI, securing cyber-physical systems in healthcare, and digitizing wellness through electronic health records (EHRs) and electronic medical records (EMRs) are also discussed. The book concludes with an extensive case study comparing the impacts of various healthcare applications, offering insights and encouraging further research and innovation in this dynamic field. Audience This book is suitable for academicians and professionals in health informatics, bioinformatics, biomedical science and engineering, artificial intelligence, as well as clinicians, IT specialists, and policymakers in healthcare.